How to Make an Image And Face Recognition App
The app that recognizes faces no longer sounds like a miracle. Although it used to sound so, and in the recent past.
Yes, thanks to the development of innovative technologies, miracles disappear from our lives one by one and become common everyday occurrences... and it's not so bad since in return we get a chance to benefit from these great achievements. And this also applies to facial recognition software.
The area is still quite new, but many companies have already managed to profit from it. That’s why the market is saturated with popular face recognition apps which have attracted numerous loyal users and started making good money. And if you also want to carve out your own piece of the pie, take your time to read our article carefully.
You'll learn about the purpose of face recognition systems, understand how they work, find out a few efficient development options, acquaint yourself with the best facial recognition apps, and get other relevant information on the topic.
What is facial recognition technology?
So, what is a face recognition system? In fact, we're talking about an online or mobile program able to isolate a human face in an image or video and even determine the identity of a person it belongs to. By the way, the software can recognize other objects in the same way either (which will be discussed below).
Current face recognition apps identify such details as:
sex of the person;
his approximate age;
Face recognition programs on the world stage
According to Bloomberg, by 2022, the global facial recognition market will have grown to 7.76 billion US dollars (from 4.05 billion dollars in 2017).
And in this regard, it'd be interesting to find out where in the world people earn on face recognition software (apps, websites, and other programs) most. The chart below answers the question.
Well, the trend seems promising, right? It’s high time we’ve delved into the issue.
Visual detection and recognition: what is the difference?
Someone might think detection and recognition are equivalent concepts, but there is a difference, and it’s crucial.
Detection is a much simpler process: the software simply determines the presence of any (!) human face in the picture or video. We're not talking about the identification of a person.
The program will just inform you: yes, here is a human face. But it won't answer the question to which person the specified face belongs. At best, you'll find out his (or her) age and gender. In order to get all the necessary information, you need to resort to recognition technology.
To make the facial recognition system work as efficiently as possible, you must access a powerful base of human faces with which your program will compare an identifiable object. The key goal is to find some unique elements peculiar to this particular person.
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Image recognition apps
As we’ve already mentioned, such programs can identify not only faces but also other well-known objects: food, furniture, animals, and so on... you never know! There are a lot of ideas of the sort.
The main thing is to remember: if you want your image identification app to be able to recognize a certain object in the photo/video in addition to detecting it, make sure your database is quite extensive and keeps growing.
How does an image or facial recognition system work?
Image detection and recognition, as a rule, comes down to pixel processing and picture matching (the source pic with the target one).
Speaking of facial recognition technology, the story is similar. This is the process of comparing a person caught in the camera lens with a database of previously saved and identified face images.
What is required for the technology of human face recognition?
To make a face recognition mobile app (or website) work, you need several components:
a video camera (which is not a problem, now all smartphones and most tablets are equipped with cameras);
a powerful server on which the database will be stored;
the effective comparison and recognition algorithm;
a trained neural network with access to millions of images with special notes.
Ways of identifying a person's face
2D recognition, a very demanded approach to face recognition at the moment. It's based on using and comparing 2-dimensional images.
3D recognition. The method is gaining popularity, although so far inferior to the previous one. It takes advantage of reconstructing three-dimensional pictures. Among the most famous 3D scanners is Apple's Face ID.
Face recognition in a controlled background. The recognition model is fairly simple, it assumes that the background is motionless and controllable. In such a case, a face identification app will have no problems with isolating separate elements (say, the eyes, nose, and so on) and reconstructing the whole object (a human face).
Color-based face search. The software scans the image in order to find areas with typical skin color and tries to catch, analyze, and identify the face segments.
Face detection by skin texture. Here we’re dealing with high-resolution images that allow a meticulous examination of the skin texture, down to lines, wrinkles, and pores.
Face search by motion. It's about video images with the motion effect. In this case, the software should look for specific reference points, such as blinking eyes, eyebrows, nostrils, forehead or mouth. As soon as any of these elements is detected, the program tries to model and identify the face and compare it with those present in the database.
The thermal imaging face recognition. Thermal imaging cameras have increasingly been used recently to identify human faces. Moreover, the area is actively developing from year to year.
Face Recognition Stages
To create a mobile app for face recognition, you have to get a clue of the steps you need to take to proceed. What stages does the identification process actually consist of?
Initial Face Detection. At the 1st stage, the system must detect the face in the image. So far, this is not about identifying a person, just the fact itself: you’re looking at a human face. And if the idea to create a face detection app satisfies you, if you don't need anything more complicated, then the following steps are less of an interest to you. Otherwise, keep reading.
Reference Points Determination. Now there is more delicate work to be done. The program finds reference points (features) on the face: those that are able to determine the individual characteristics of a person. Previously, the eyes were considered the main reference point, but now the calculation technology has been significantly improved to include almost 70 key features.
Frontal Face Building. To facilitate the process of matching objects, the face should be adjusted so as to obtain its frontal image.
Feature Descriptor Calculation. Now the descriptor is being calculated, which is a set of features describing the person’s face, regardless of such factors as age, hairstyle, etc. To be precise, we should get a certain digital portrait, a face vector to make a further comparison possible.
Face Comprasion. The 5th stage involves the process of comparing the resulting digital face vector with the objects stored in the database.
Face Recognition, the final identification of the person (o, rather, his/her face) after the found match.
Again, all of the above can apply not only to faces but to any items. The main thing is to set up an algorithm, which will recreate the desired object from the pixels and compare it with the database in order to find matches.
We figured out how it all works, but you probably care about another question: what is the purpose of facial recognition when it comes to business?
What is facial recognition used for?
To build a face recognition mobile application (or image identification app), you must know which markets to focus on. We offer you a couple of cool ideas, and one of them might interest you.
Take a close look at the following examples.
Today people are conditionally divided into 2 opposing camps, figuratively speaking: some follow a new body-positive trend, others lead a healthy lifestyle and monitor their nutrition. And the second group will definitely like applications aimed at helping them in counting calories and determining the nutritional value of products.
Imagine how easy it would be to calculate the calorie content of products if all you need to do is take a picture of your dish and ask the program to analyze it. Do you think it's impossible? However, such applications do exist. One of them is Calorie Mama, a really good and helpful image recognition app. Its extensive database contains a great many dishes with detailed information on each so that the user can find out the nutritional value of his diet in no time.
Of course, Google with its popular Image Search immediately comes to our mind.
Google technology is able to search for pictures on a given one. This means you may upload your image and find sites having its copies.
Just remember, Google Image Search doesn't use facial recognition technology; though, its engine algorithms are accurate enough to provide desired results anyway.
Here we take advantage of the same approach as above. Only in this case, the user gets the opportunity to buy the desired product (the one shown in the picture).
A good example of such an application is ScreenShopit offering to use its API so that online stores can simplify their product search systems. The service is based on machine learning, which makes it very efficient.
Another instance of a shopping image identification app is CamFind with its Visual Search engine. It allows you to take a picture of any object, upload it to the program, and find one of the items in the list below:
the desired product in stores;
image-related online content;
and so on.
In addition, there is a possibility to share search results with each other and track user finds.
Environment and nature
Also, image recognition apps would be useful to those who are keen on gardening, working with the environment or dealing with nature in some other way.
Say, such a person encounters a plant unknown to him and wants to find out its name, properties and get other similar information. He can take a picture of his herb example and upload it to the application, which is going to provide him with all the necessary data.
Language applications based on image and facial recognition technology work in a similar way and help users seamlessly expand their vocabulary.
Take a look at ImageTranslate, if you need a good example. It’s quite easy: you upload a photo, make a couple of taps, and get a translation of the object depicted on it.
We talked about the identification of objects, and now we’d like to bring to your attention what is the best face recognition app for iPhone and Android. Or at least which applications are among the market leaders:
Betaface, the program targeted at media companies. The application helps in finding people and getting information about them (if such data can be found on the Internet). Also, Betaface allows searching for a similar person in the celebrity database or on Wikipedia. And one more thing: each photo is marked with a percentage of the match level.
Blippar. In fact, Blippar is more than just a face comparison app; it is a real AR browser. However, its latest versions began to support a facial recognition feature either. The application is able to “recognize” the user and find his profiles on social networks, as well as get affordable information about his hobbies, preferences and more.
We’ve listed the main solutions aimed at image & face recognition in mobile app development. However, this is far from all the possibilities. We offer a couple more promising ideas:
Access to various systems. According to J'son & Partners, since 2014, the share of access control systems with face recognition has grown from 0.7% to 11%. A prime example is Apple's FaceID. Thanks to the face recognition feature, only the smartphone owner gets access to the functionality of a particular application.
Bank Identification. A face recognition app for Android and iOS may come in handy in the banking sector either. Over the years, financial institutions around the world have been actively collecting customer biometric data. So today many banks provide clients with special software, which allows authenticating with the system through voice and images. Therefore, users are able to remotely open an account, order a card issue, and so on.
Access to exams and educational programs. Modern European and American educational institutions often practice a system of training and testing students using remote identification. It means students may take advantage of offered software to gain access to the course materials. Sometimes they even get a chance to pass their exams remotely, whereas previously it wasn't possible due to the use of the standard password access mechanism. Face recognition solutions and tools are more reliable in this respect.
How to make a mobile app for face recognition?
The key question is probably this one: how to make a face recognition app? What tools would you need to bring your idea to life?
There are many options, we’ll describe the 3 most popular of them.
The easiest way to create a face recognition software for Android or iOS is to resort to the help of Native APIs from Apple and Google. It’s affordable, easy to implement, requires no extra costs and effort. Of course, there won't be too many features, but, who knows, maybe they'll be just enough to achieve the desired.
The second option is to use third-party solutions. And let us say, the variety of choices of these tools will surprise you with its hugeness: many companies offer their APIs to create a face detection app. How about these ones?
Amazon has a lot of development products (including a shopping platform and cloud solutions), and a Visual Recognition API is among them. Moreover, there are both paid and free options.
Luxand.cloud API helps to develop applications able to determine human sex, age, emotional state, and more. The company ensures 3 price packages: BASIC, PRO, and ULTRA.
FaceMark, a very simple and reliable API solution: it provides a lot of reference points to recreate the full face and profile, promises ease of use, and offers several pricing models.
In the case of third-party solutions, the cost of face recognition mobile apps may be different. It all depends on your choice.
OpenCV (Open Source Computer Vision Library)
Our list concludes with a solution called OpenCV.
OpenCV is a library with more than 2.5 thousand carefully optimized and adapted algorithms, both classic and modern ones. They’re focused on computer vision and machine learning and can be used to identify images (which includes recognition of human faces), track moving items, extract 3D models of objects, and much more in the same way.
OpenCV is a licensed BSD product, which makes the work on the code greatly simplified.
Now you know all you need about creating a custom face recognition app. The rest is up to the developers you’ll hire. It is with them that you should discuss your project features, draw up a plan, and get down to business.
And make sure you've found an experienced team capable to overcome any difficulties. The company you collaborate with should be ready to face all the challenges of the development of a mobile application for face recognition.